Assessing variation in population abundance over time and across space is a long-standing goal of population ecologists. Up to now, two main approaches have been mostly used to identify the factors driving observed fluctuations in population abundance. First, a pattern-oriented approach, based on the monitoring of population size, involves the analysis of time series of counts. In the most recent applications, these analyses lead to partitioning observed changes in population growth into different contributing factors, like current or past population density, environmental conditions, or demographic stochasticity. Second, a process-oriented approach, based on the monitoring of demographic parameters, involves the construction of age- or stage-structured demographic models. The steady increase of case studies aiming to monitor known-aged recognizable animals over most of their lifespan, the availability of statistical methods allowing reliable estimates of demographic parameters to be obtained from field data, and the development of a powerful framework to build a large range of matrix population models have all led to this process-oriented approach becoming a standard tool of population ecologists. It has become the gold standard in the context of both the management of exploited populations and the conservation of endangered populations. However, analyses of detailed monitoring of individuals have also revealed the existence of marked individual differences in most life history traits studied so far, which have been mostly ignored until now when using population-scale demographic modelling. To account for such sources of within-population variation, a trait-based demographic approach is required. Nowadays, Integral Projection Models (IPMs) provide a way to obtain more realistic demographic models that encompass the association between demographic parameters and, for instance, phenotypic traits. In their most extended version, IPMs include the four biological functions that are necessary and sufficient to obtain the distribution of a given continuous trait in a population at a given time from the distribution of the same trait in the same population one time-step before. These functions are the survival function linking survival probability to the trait value, the recruitment function linking the number of recruits to the trait value, the growth function linking the trait value at time t+1 to the trait value at time t, and the inheritance function linking the trait value of the offspring to the trait value of the parents.

Following the British Ecological Society Symposium “Demography Beyond the Population” that was held in Sheffield about one year ago, four papers derived from this symposium have just been published in Journal of Animal Ecology as part of the British Ecological Society Cross Journal Special Feature: Demography Beyond the Population. From the analysis of the contents of these four papers it appears that a new, integrated demography, comes of age. Continue reading “Demography beyond the population: Integrated demography comes of age”